Content¶

1. Prerequisites

2. Download the PROFFASTpylot repository

3. Get PROFFAST and copy it to proffastpylot

4. Create a virtual environment in python

5. Install PROFFASTpylot

6. Resulting folder structure

7. Test the installation by running an example dataset

8. Getting Updates

1. Prerequisites¶

For using PROFFASTpylot you need Python 3.7 or newer. The PROFFAST and PROFFASTpylot can be used in Windows and Linux environments. A step-by-step installation instruction for both environments is given in the following. We did not test the software for Mac environments.

2. Download the PROFFASTpylot repository¶

git clone https://gitlab.eudat.eu/coccon-kit/proffastpylot.git

3. Get PROFFAST and copy it to the proffastpylot folder¶

cd prf/
bash install_proffast_linux.sh

4. Create a virtual environment in python¶

We recommend using a virtual environment (venv) to avoid conflicts between any other packages or Python modules.

1. (Only first time) Navigate to the proffastpylot folder using a terminal.

2. (Only first time) Enter python -m venv prf_venv.
   This command will create a folder named prf_venv which contains the virtual environment

3. Activate the virtual environment every time you run PROFFASTpylot with

   • Windows PowerShell: .\prf_venv\Scripts\Activate.ps1

   • Windows Commandline: .\prf_venv\Scripts\activate

   • Linux: source prf_venv/bin/activate

4. To deactivate the virtual environment you can run deactivate

Note that all packages to be installed with pip install will only affect the virtual environment and not the local Python installation.
In case of a problem, take a look at the Troubleshooting article of this documentation.

You need to activate the virtual environment before each run of PROFFASTpylot by executing the command in step 3, the other steps need to be executed only the first time.

5. Install the PROFFASTpylot repository¶

Activate the virtual environment (see above).

Navigate to proffastpylot and enter

pip install --editable .

6. Resulting folder structure¶

If you follow exactly the installation guide your folder structure should look like the following:

proffastpylot
├── prf_venv
│   ├── ...
├── docs
│   ├── ...
├── example
│   ├── input_sodankyla_example.yml
│   ├── log_type_pressure.yml
│   └── run.py
├── prf
│   ├── docs
│   ├── inp_fast
│   ├── inp_fwd
│   ├── preprocess
│   ├── source
│   ├── out_fast
│   └── wrk_fast
├── prfpylot
│   ├── ...
└── setup.py

7. Test the installation by running an example dataset¶

To test the installation, we provide example raw data and a reference result file to compare the file to. The example can be executed by navigating to the example folder and execute python run.py (please ensure that your virtual environment is activated).
When first running the program, it will ask you to download the example file data to your local computer.

After the run is complete, please compare your results to the data given in example\Reference_Output_Example_Sodankyla.csv. The deviations should be less than 0.1 ppm for XCO2, 0.1 ppb for XCH4 and 0.1 ppb for XCO.

8. Getting Updates¶

If you used git during installation, you can easily get updates by entering

git pull

in a git bash or in a Terminal in your proffastpylot folder. This command will download all available updates. If you downloaded PROFFASTpylot as zip file, you need to redo all steps of this installation script.